---
library_name: transformers
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert-math-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# camembert-math-classification

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3711
- F1 Macro: 0.9159
- F1 Weighted: 0.9139
- F1 Correct: 1.0
- F1 Partiel: 0.8953
- F1 Incorrect: 0.8525
- Accuracy: 0.9143

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Correct | F1 Partiel | F1 Incorrect | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:----------:|:----------:|:------------:|:--------:|
| 1.0746        | 1.0   | 53   | 0.8969          | 0.7007   | 0.7086      | 0.8227     | 0.7795     | 0.5          | 0.7381   |
| 0.7178        | 2.0   | 106  | 0.5763          | 0.8772   | 0.8761      | 0.9767     | 0.8663     | 0.7885       | 0.8810   |
| 0.5751        | 3.0   | 159  | 0.4265          | 0.9180   | 0.9169      | 1.0        | 0.9071     | 0.8468       | 0.9190   |
| 0.4558        | 4.0   | 212  | 0.3711          | 0.9159   | 0.9139      | 1.0        | 0.8953     | 0.8525       | 0.9143   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2